How to use AI technology to measure and change culture

digital transformation and culture change

AI technology has the potential to give both the Board and executive teams visibility and measures to understand more about the culture within their business – and more importantly, how to change it, writes Alec Bashinsky

The Hayne Royal Commission has undoubtedly delivered one major outcome: our banks and indeed many organisations do not know how to measure their culture effectively.

Artificial intelligence is now manifesting insitself in many forms in the HR world, from chatbots in prescreening recruitment process to algorithms that drive talent analytics.

However, I believe that many organisations still do not know how to measure let alone change their culture. Employee engagement surveys are definitely not effective as their questions are in my view not relevant, the answers can be gamed, the frequency is inefficient and the results are static rather than being regularly pulsed for accurate analysis – and they do not measure culture.

Now I know from personal experience, some people are more influential than others. The good thing, however, in today’s digital talent disruption world is that there is AI technology available where you can actually measure someone’s influential reach in an organisation.

The method used for this is called Organizational Network Analysis (ONA) and in my view is indeed the most effective way to measure, predict and monitor culture.

“Some organisations just appoint their change agents based on their title or role within the business, expecting them to influence and drive change”

This scientific methodology has been rigorously tested in the business environment by many researchers and practitioners for more than a quarter of a century. Professor Peter Gloor from Massachusetts Institute of Technology (MIT) the doyen in ONA research, development and use of artificial intelligence for over 20 years, has developed this approach from his early work utilising the Enron data which became public to test his methodology and algorithms.

This involves the deployment of a unique machine ONA tool to identify network influencers and analyse the way that influence is being used.

ONA data can then be used to coach high performers, identify leadership candidates, and better pre-empt departures by talking with people well before they leave. It can also provide signals for executives as to when behaviour isn’t working within a business unit, ie silo mentalities and perhaps, more importantly, measuring culture within an organisation.

For example, some organisations just appoint their change agents based on their title or role within the business, expecting them to influence and drive change. There are challenges that come with this approach, such as not knowing their actual employee’s influence or reach, not being transparent, creating internal tension, and so on.

“All organisations including banks should be looking at alternative approaches to the digitisation of business models and strategy”

However, utilising ONA technology, companies now can identify the right change agents in a scientifically and business proven way.

Harvard Business Review has found that more than 50 per cent of influencers are typically unknown to management. This gives you an idea of how much you are missing by appointing change agents within companies without using ONA. The real magic happens when you add influencers to the number of employees they reach. Including them, management can have more than three-quarters of employees focusing on the same objective. That’s enough to seriously accelerate digital transformation and for the banks focus on risk, governance and culture behaviours.

I’m sure that all the banks are being flooded with ‘culture change experts’ who all have different views on how to change culture. In my view, unless you have been in an organisation and developed and implemented culture change that has worked, then you are in no position to advise – and in many cases, consultants are only driving their methodology for change and haven’t successfully implemented this in an organisation.

All organisations including banks should be looking at alternative approaches to the digitisation of business models and strategy. These technologies (AI, data science, social media, and so on) have the potential to provide great benefit and give both the Board and executives teams visibility and measures to understand more about their culture within their business – and more importantly, how to change it.